SPATIAL CHANNEL COVARIANCE ESTIMATION FOR THE HYBRID ARCHITECTURE AT A BASE STATION: A TENSOR-DECOMPOSITION-BASED APPROACH

Abstract

Spatial channel covariance information can replace instantaneous full channel state information for designing hybrid analog/digital precoders. Estimating the spatial channel covariance is challenging due to the inherent limitation of the hybrid architecture, i.e., much fewer radio frequency (RF) chains than antennas. In this paper, we propose a spatial channel covariance estimation method for spatially sparse time-varying frequency-selective channels. The proposed method leverages the fact that the channel can be represented as a low-rank higher-order tensor. Numerical results demonstrate that the proposed approach achieves higher estimation accuracy in comparison with existing covariance estimation methods.